Position statement: The case for a visualization performance benchmark

L. Battle, Remco Chang, Jeffrey Heer, M. Stonebraker
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引用次数: 17

Abstract

Visualizations are an invaluable tool in the data analysis process, as they enable scientists to explore and interpret billions of datapoints quickly, and with just a few rendered images. However, many visualization systems are unable to keep up with the unprecedented accumulation of data through remote sensors, field sensors, medical and personal devices, social networks, and more. This is due to certain assumptions that many of these tools rely on, such as the assumption that these systems can store entire datasets directly in main memory. With so many datasets massive datasets available, ranging from the NASA MODIS satellite imagery dataset[3] to the Internet Movie Database [4] to Twitter streams [1], this assumption no longer matches reality.
立场声明:可视化性能基准的案例
可视化是数据分析过程中非常宝贵的工具,因为它们使科学家能够快速探索和解释数十亿个数据点,并且仅使用少数渲染图像。然而,许多可视化系统无法跟上来自远程传感器、现场传感器、医疗和个人设备、社交网络等的前所未有的数据积累。这是由于许多这些工具所依赖的某些假设,例如假设这些系统可以将整个数据集直接存储在主存中。从NASA MODIS卫星图像数据集[3]到互联网电影数据库[4],再到Twitter流[1],有如此多的数据集可供使用,这种假设不再符合现实。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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